What is structured data?
schema markup, schema.org, JSON-LD
Structured data is code added to a web page, usually schema.org vocabulary written in JSON-LD, that labels what the page contains: a product and its price, an organization and its logo, an article and its author, or a list of FAQs. It helps search engines and AI systems read your facts accurately instead of guessing.
Structured data labels page facts in a format machines read reliably.
JSON-LD with schema.org types is the format Google recommends.
Markup must match visible content, or it can hurt more than help.
How structured data works
Structured data works by adding a machine-readable description of a page alongside the human-readable content. The most common format is JSON-LD, a block of JSON inside a script tag in the page HTML. It uses the schema.org vocabulary, a shared set of types and properties backed by the major search engines.
For example, a product page might include a Product object with properties such as name, brand, offers (price, currency, availability) and aggregateRating. A search engine reading that block knows the price is a price, not just a number on the page.
Search engines use structured data to understand entities, show rich results and feed their knowledge graph. AI systems that draw on those indexes benefit from the same clarity when they describe your products and company.
Common structured data types
The most useful structured data types depend on what your site offers. Common schema.org types include:
Organization: your name, logo, website, social profiles and contact points. Helps establish your brand as an entity.
Product and Offer: product name, brand, SKU, price, currency and stock status. Essential for e-commerce and AI shopping.
Review and AggregateRating: ratings and review counts tied to a product or business.
Article: headline, author, publish date and modified date.
FAQPage: questions and answers shown on a page.
LocalBusiness: address, opening hours and service area for physical locations.
BreadcrumbList: where the page sits in your site structure.
Start with Organization on your homepage and the type that matches your core page templates, then expand from there.
Does structured data help AI search?
Structured data helps AI search indirectly, by making your facts easier to extract and harder to misread. AI engines have not published how much weight they give schema markup when choosing sources. What is clear is that many AI answers draw on search indexes, product feeds and knowledge graphs that use structured data.
The benefit is strongest for facts that change or are easy to confuse: prices, availability, ratings, dates, authors and company details. Clear markup supports entity SEO by linking your brand to consistent attributes, and it can reduce the risk of AI hallucinations about details like price or stock.
Structured data is not a substitute for clear visible content. Engines still read the page text, so every important fact should appear in both places.
How to implement structured data
Implementing structured data well means accurate markup on the right pages, kept in sync with what users see.
Choose types that match each page template, such as Product for product pages and Article for blog posts.
Use JSON-LD in the page HTML, ideally through server-side rendering so crawlers that skip JavaScript still see it.
Match visible content: never mark up prices, reviews or FAQs that are not on the page.
Generate from your data source: pull prices and stock from the same database as your product feeds so everything updates together.
Validate with the Schema Markup Validator and the Google Rich Results Test.
Monitor for errors after site releases, since template changes often break markup.
How KIME checks structured data for AI
KIME AI Web Health reviews how readable your site is for AI engines, including technical signals like structured data that help models understand your products and brand. Gaps become technical tasks in Actions, ranked by expected impact. For e-commerce brands, pairing this with KIME Shopping shows whether better product data lines up with more appearances in AI shopping answers over time.
Frequently asked questions
What is the difference between schema markup and structured data?
Structured data is the general idea of labeling page content in a machine-readable format. Schema markup usually means structured data that uses the schema.org vocabulary, which is the standard most search engines support. In everyday SEO use, the two terms are often treated as the same thing, with JSON-LD as the most common format.
Does FAQ schema still matter?
FAQPage markup still helps machines understand question-and-answer content, even though Google limited FAQ rich results in 2023 to a small set of authoritative government and health sites. For AI search, the value lies mainly in clear question-and-answer structure on the page itself. Markup adds a consistent label, but the visible answers do most of the work.
Can structured data hurt my site?
Structured data can cause problems when it is wrong or misleading. Marking up reviews, prices or content that users cannot see breaks Google guidelines and can lead to a manual action that removes rich results. Outdated markup, such as an old price, can also spread incorrect facts, so generate markup from the same data as the visible page.